IκBζ facilitates protective immunity against Salmonella infection via Th1 differentiation and IgG production
Bibliographic record
Abstract
Abstract Inhibitor of kappa B (IκB)-ζ transcription is rapidly induced by stimulation with TLR ligands and IL-1. Despite high IκBζ expression in inflammation sites, the association of IκBζ with host defence via systemic immune responses against bacterial infection remains unclear. Oral immunisation with a recombinant attenuated Salmonella vaccine (RASV) strain did not protect IκBζ-deficient mice against a lethal Salmonella challenge. IκBζ-deficient mice failed to produce Salmonella LPS-specific IgG, especially IgG2a, although inflammatory cytokine production and immune cell infiltration into the liver increased after oral RASV administration. Moreover, IκBζ-deficient mice exhibited enhanced splenic germinal centre reactions followed by increased total IgG production, despite IκBζ-deficient B cells having an intrinsic antibody class switching defect. IκBζ-deficient CD4+ T cells poorly differentiated into Th1 cells. IFN-γ production by CD4+ T cells from IκBζ-deficient mice immunised with RASV significantly decreased after restimulation with heat-killed RASV in vitro, suggesting that IκBζ-deficient mice failed to mount protective immune responses against Salmonella infection because of insufficient Th1 and IgG production. Therefore, IκBζ is crucial in protecting against Salmonella infection by inducing Th1 differentiation followed by IgG production.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".